This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations. To enable the following instructions: FMA, i

Description

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Environment

TensorRT Version: 10.0
GPU Type: 4
Nvidia Driver Version: 535
CUDA Version: 12.4
CUDNN Version: 12.4
Operating System + Version: ubuntu server 22.04
Python Version (if applicable): python3
TensorFlow Version (if applicable): 2.16
PyTorch Version (if applicable):
Baremetal or Container (if container which image + tag):

Relevant Files

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Steps To Reproduce

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  • Full traceback of errors encountered

ure_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-04-22 08:12:25.606617: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
2024-04-22 08:12:26.270155: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:998] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at linux/Documentation/ABI/testing/sysfs-bus-pci at v6.0 · torvalds/linux · GitHub
2024-04-22 08:12:26.322857: W tensorflow/core/common_runtime/gpu/gpu_device.cc:2251] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at Install TensorFlow with pip for how to download and setup the required libraries for your platform.
Skipping registering GPU devices…
Num GPUs Available: 0
root@server1:/opt# cat tensorflow/compiler/tf2tensorrt/utils/py_utils.cc |less
cat: tensorflow/compiler/tf2tensorrt/utils/py_utils.cc: No such file or directory
root@server1:/opt#